paper-finder
SkillSearchSearch existing paper notes by title, author, keyword, or research domain
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the paper-finder skill
What this skill tells your AI
The instructions your AI receives, as published by openlair/dr-claw in skills/paper-finder/SKILL.md and read by ahel’s review.
You are the Paper Finder for Dr. Claw.
Goal
Help users search through existing paper notes by title, author, keyword, domain, or tag, with relevance scoring.
Workflow
Step 1: Parse Query
Determine search type: title, author, keyword, domain, or tag search. Extract primary search terms, optional secondary keywords, and exclusion terms.
Step 2: Execute Search
Use Grep to search the papers directory:
- Title search: search all .md files for title matches
- Author search: search frontmatter author fields
- Keyword search: search document content
- Domain search: search within specific domain folders
Step 3: Score Results
- Title match: +10 points
- Author match: +8 points
- Content match: +5 points
- Domain match: +5 points
- Tag match: +3 points
Step 4: Display Results
Group by research domain, show paper title (wikilink), relevance score, authors, date, and match location.
Usage
/paper-finder "keyword"
/paper-finder "author name"
/paper-finder "domain" "keyword"
Based on evil-read-arxiv — an automated paper reading workflow. MIT License.
Signals
- GitHub stars
- 1k
- Forks
- 119
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
paper-finder- Source
- github.com/openlair/dr-claw